This work presents a Fuzzy Logic Controller （FLC） assigned to control a robotic arm motion while avoiding the obstacles that may face the robotic arm in its movement from the initial point to the final point in an o...This work presents a Fuzzy Logic Controller （FLC） assigned to control a robotic arm motion while avoiding the obstacles that may face the robotic arm in its movement from the initial point to the final point in an optimized manner, in addition to avoid the singularity phenomenon, and without any exceeding of the physical constraints of the robot arm. A real platform （5 DOF ＂Degree Of Freedom＂ Lab Volt 5150 Robotic Arm） is used to carry this work practically, in addition to providing it by a vision sensor, where a new approach is proposed to inspect the robot work environment using a designed integrated MATLAB program having the ability to recognize the changeable locations of each of the robotic arm＇s end-effector, the goal, and the multi existed obstacles through a recorded film taken by a webcam, then these information will be treated using the FLC where its outputs represent the values that must be delivered to the robot to adopt them in its next steps till reaching to the goal in collision-free movements. The experimental results showed that the developed robotic ann travels successfully from Start to Goal where a high percentage of accuracy in arriving to Goal was achieved, and without colliding with any obstacle ensuring the harmonization between the theoretical part and the experimental part in achieving the best results of controlling the robotic arm＇s motion.展开更多
Pedestrian detection is one of the most important problems in the visual sensor network. Considering that the visual sensors have limited cap ability, we propose a pedestrian detection method with low energy consumpti...Pedestrian detection is one of the most important problems in the visual sensor network. Considering that the visual sensors have limited cap ability, we propose a pedestrian detection method with low energy consumption. Our method contains two parts: one is an Enhanced Self-Organizing Background Subtraction (ESOBS) based foreground segmentation module to obtain active areas in the observed region from the visual sensors; the other is an appearance model based detection module to detect the pedestrians from the foreground areas. Moreover, we create our own large pedestrian dataset according to the specific scene in the visual sensor network. Numerous experiments are conducted in both indoor and outdoor specific scenes. The experimental results show that our method is effective.展开更多
文摘This work presents a Fuzzy Logic Controller （FLC） assigned to control a robotic arm motion while avoiding the obstacles that may face the robotic arm in its movement from the initial point to the final point in an optimized manner, in addition to avoid the singularity phenomenon, and without any exceeding of the physical constraints of the robot arm. A real platform （5 DOF ＂Degree Of Freedom＂ Lab Volt 5150 Robotic Arm） is used to carry this work practically, in addition to providing it by a vision sensor, where a new approach is proposed to inspect the robot work environment using a designed integrated MATLAB program having the ability to recognize the changeable locations of each of the robotic arm＇s end-effector, the goal, and the multi existed obstacles through a recorded film taken by a webcam, then these information will be treated using the FLC where its outputs represent the values that must be delivered to the robot to adopt them in its next steps till reaching to the goal in collision-free movements. The experimental results showed that the developed robotic ann travels successfully from Start to Goal where a high percentage of accuracy in arriving to Goal was achieved, and without colliding with any obstacle ensuring the harmonization between the theoretical part and the experimental part in achieving the best results of controlling the robotic arm＇s motion.
基金This paper was supported partially by the Natural Science Foundation of China under Grants No. 60833009, No. 61003280 the National Science Fund for Distinguished Young Scholars under Grant No. 60925010+1 种基金 the Funds for Creative Research Groups of China under Grant No.61121001 the Pro- gram for Changjiang Scholars and Innovative Research Team in University under Grant No. IRT1049.
文摘Pedestrian detection is one of the most important problems in the visual sensor network. Considering that the visual sensors have limited cap ability, we propose a pedestrian detection method with low energy consumption. Our method contains two parts: one is an Enhanced Self-Organizing Background Subtraction (ESOBS) based foreground segmentation module to obtain active areas in the observed region from the visual sensors; the other is an appearance model based detection module to detect the pedestrians from the foreground areas. Moreover, we create our own large pedestrian dataset according to the specific scene in the visual sensor network. Numerous experiments are conducted in both indoor and outdoor specific scenes. The experimental results show that our method is effective.
